R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(17192.4,15386.1,14287.1,17526.6,14497,14398.3,16629.6,16670.7,16614.8,16869.2,15663.9,16359.9,18447.7,16889,16505,18320.9,15052.1,15699.8,18135.3,16768.7,18883,19021,18101.9,17776.1,21489.9,17065.3,18690,18953.1,16398.9,16895.6,18553,19270,19422.1,17579.4,18637.3,18076.7,20438.6,18075.2,19563,19899.2,19227.5,17789.6,19220.8,21968.9,21131.5,19484.6,22168.7,20866.8,22176.2,23533.8,21479.6,24347.7,22751.6,20328.3,23650.4,23335.7,19614.9,18042.3,17282.5,16847.2,18159.5)
> par1 = '4'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 61
> (np <- floor(n / par1))
[1] 15
> arr <- array(NA,dim=c(par1,np))
> j <- 0
> k <- 1
> for (i in 1:(np*par1))
+ {
+ j = j + 1
+ arr[j,k] <- x[i]
+ if (j == par1) {
+ j = 0
+ k=k+1
+ }
+ }
> arr
        [,1]    [,2]    [,3]    [,4]    [,5]    [,6]    [,7]    [,8]    [,9]
[1,] 17192.4 14497.0 16614.8 18447.7 15052.1 18883.0 21489.9 16398.9 19422.1
[2,] 15386.1 14398.3 16869.2 16889.0 15699.8 19021.0 17065.3 16895.6 17579.4
[3,] 14287.1 16629.6 15663.9 16505.0 18135.3 18101.9 18690.0 18553.0 18637.3
[4,] 17526.6 16670.7 16359.9 18320.9 16768.7 17776.1 18953.1 19270.0 18076.7
       [,10]   [,11]   [,12]   [,13]   [,14]   [,15]
[1,] 20438.6 19227.5 21131.5 22176.2 22751.6 19614.9
[2,] 18075.2 17789.6 19484.6 23533.8 20328.3 18042.3
[3,] 19563.0 19220.8 22168.7 21479.6 23650.4 17282.5
[4,] 19899.2 21968.9 20866.8 24347.7 23335.7 16847.2
> arr.mean <- array(NA,dim=np)
> arr.sd <- array(NA,dim=np)
> arr.range <- array(NA,dim=np)
> for (j in 1:np)
+ {
+ arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
+ arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
+ arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
+ }
> arr.mean
 [1] 16098.05 15548.90 16376.95 17540.65 16413.97 18445.50 19049.58 17779.38
 [9] 18428.88 19494.00 19551.70 20912.90 22884.33 22516.50 17946.72
> arr.sd
 [1] 1530.2254 1272.3629  518.8493  988.0534 1348.2753  602.4295 1828.5819
 [8] 1354.8958  790.6900 1012.2929 1747.6129 1105.5897 1295.8880 1505.5795
[15] 1216.8391
> arr.range
 [1] 3239.5 2272.4 1205.3 1942.7 3083.2 1244.9 4424.6 2871.1 1842.7 2363.4
[11] 4179.3 2684.1 2868.1 3322.1 2767.7
> (lm1 <- lm(arr.sd~arr.mean))

Call:
lm(formula = arr.sd ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
  551.71597      0.03528  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))

Call:
lm(formula = log(arr.sd) ~ log(arr.mean))

Coefficients:
  (Intercept)  log(arr.mean)  
       0.4420         0.6717  

> (lm2 <- lm(arr.range~arr.mean))

Call:
lm(formula = arr.range ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
   398.7323       0.1231  

> postscript(file="/var/www/html/rcomp/tmp/1pnj71260629780.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2jpgc1260629780.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Section',header=TRUE)
> a<-table.element(a,'Mean',header=TRUE)
> a<-table.element(a,'Standard Deviation',header=TRUE)
> a<-table.element(a,'Range',header=TRUE)
> a<-table.row.end(a)
> for (j in 1:np) {
+ a<-table.row.start(a)
+ a<-table.element(a,j,header=TRUE)
+ a<-table.element(a,arr.mean[j])
+ a<-table.element(a,arr.sd[j] )
+ a<-table.element(a,arr.range[j] )
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/3q9n41260629780.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4j99c1260629780.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Lambda',header=TRUE)
> a<-table.element(a,1-lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5rm6q1260629780.tab") 
> 
> try(system("convert tmp/1pnj71260629780.ps tmp/1pnj71260629780.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jpgc1260629780.ps tmp/2jpgc1260629780.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.525   0.291   2.837